Mass Analysis Of Satellite Images Aid Philippine Disaster Relief

DigitalGlobe serves up satellite imagery to crowd community to analyze Typhoon Haiyan's destruction.

A leading satellite image provider is offering it’s imaging capabilities -- and appealing to the power of crowdsourcing -- to help make sense of Typhoon Haiyan’s destructive assault on the Philippines.

Hours before the storm hit on November 7, DigitalGlobe activated its FirstLook online subscription service to provide web-based access to pre- and post-storm images of the islands. The company's satellites captured images of more than 19,000 square kilometers in the hardest-hit areas.

Nightly news programs in the days since the storm show buildings in ruins, refugees sheltering wherever they can, and relief workers trying to provide medical care, food and water when there is no infrastructure in place.

But trying to assess the damage revealed by the satellite images -- and help relief organizers make better decisions -- is a huge undertaking, so DigitalGlobe has started an online crowdsourcing campaign inviting help from anyone who wishes to join. DigitalGlobe is a commercial supplier of space imagery and remote sensing data to NASA, the Defense Department, the National Geospatial-Intelligence Agency and other federal agencies, as well as to Google Earth.

The Tomnod platform provides access to satellite imagery of the devastated areas. Visitors can help by mapping damage caused by the storm, identifying damaged roads and bridges, damaged large buildings, flooded areas, debris fields, and damaged residential areas. When one of these categories is identified, the user tags it. DigitalGlobe uses algorithms to combine and match tags from hundreds of users, then ranks them in terms of interest and importance.

“There are over 1,500 people crowdsourcing the images,” said Shay Har-Noy, the founder of Tomnod. “They’ve identified about 150,000 points of damage.”

As the damage is assessed, the company is passing the information on to relief organizations. “We are working specifically with [non-governmental organizations] that have folks on the ground,” said Har-Noy, including the Red Cross and Team Rubicon, former Marines who travel to disaster sites to help. The company also is providing information to the US Pacific Command, which has sent the aircraft carrier George Washington and its strike group to provide disaster relief assistance.

“The most useful tags are damaged roads, damaged large buildings, and large areas of destruction,” he said. For emergency workers on the ground, the first challenge is how to move around and to find out what infrastructure -- water, sewer, electrical -- has been damaged. The satellite images help them figure out how to get where they need to go, what they will find when they get there, and what they need to bring with them.

Har-Noy said that DigitalGlobe activates FirstLook about once a week for disasters around the world, everything from wildfires and tornadoes in the United States to floods in Russia, earthquakes in China, and now the typhoon in the Philippines.

“If you can’t afford to give ten bucks, give ten minutes,” Har-Noy said. “This is about being able to unlock the value in our images, particularly in disasters when time is of the essence.

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DigitalGlobe was the same outfit that provided satellite imagery of the Pacific off the coast of San Francisco, when the highly respected researcher Jim Gray disappeared in 2007. The imagery was analyzed by volunteers, looking for 6-8 slightly darker pixels -- representing Gray's 42-foot sailboat -- out of 160,000 monochromatic gray ocean surface pixels per image. Two promising objects were identified in hundreds of square miles of ocean. The analysis of satrellite imagery through crowd-sourced volunteers to establish damage in the Philipines is another example of pushing the limits of available technology. Gray, who regretably was never found, would approve.

An excellent example of how technology can help disaster zones, and I am guessing a lot of the identification must have been done by an algorithm for example, pre-disaster roads would be mapped by an algorithm (those yellow lines over roads on Google map) and post-disaster roads would be mapped -- any changes would identify a possible region of concern that a human eye could further investigate.

If thereís one asset the U.S. government has in abundance, itís data. But a fight for expertise is hindering both the public and private sectors when it comes to managing and mining information. Can Uncle Sam compete for talent?